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Minerva Research Group

Lifespan Changes in Memory Representations

How do we remember and why do we remember less when we age?

From a neuroscientific perspective, our memories are encoded in specific distributed patterns of neural activity, that is, these patterns can be regarded as memory fingerprints. During encoding of memories, specific representational patterns are formed (e.g., meeting a person for the first time). These can be reactivated during later recall (when seeing the person again). The more similar the reactivated pattern is to the original pattern, the more likely we are to retrieve a specific memory (it is easier to recognize a person if you meet her again in a similar context). In order to achieve optimal memory performance, patterns of different memories should be distinct whereas patterns of the same memory should be as similar as possible. To render memories durable, our brain spontaneously reactivates and thus strengthens novel patterns during rest and sleep periods.

We investigate how aging affects the distinctiveness and similarity of memory representations during memory formation, maintenance, and retrieval. Specifically, we want to understand whether age-related changes in the way how information is represented in the brain has consequences for memory performance of older adults. A second line of research targets age differences in the spontaneous reactivation of memories during wakefulness and sleep.

Team photo

Current Projects

Age differences in alerting may be one reason for subsequent differences in stimulus processing. Do older adults benefit less from an unspecific warning cue than young adults?
Similarity between memory representations seems to be beneficial for memory performance of young adults, but often harmful for older adults. How consistent is this phenomenon across different levels of similarity and how does it relate to the precision of memory representations?

Publications

Sander, M. C., Fandakova, Y., Grandy, T. H., Shing, Y. L., & Werkle-Bergner, M. (2019). Oscillatory mechanisms of successful memory formation in younger and older adults are related to structural integrity. BioRxiv: 530101. https://doi.org/10.1101/530121

Sommer, V. R., Fandakova, Y., Grandy, T. H., Shing, Y. L., Werkle-Bergner, M., & Sander, M. C. (2019). Neural pattern similarity differentially affects memory performance of younger and older adults. BioRxiv: 528620. https://doi.org/10.1101/528620

Fandakova, Y., Sander, M. C., Grandy, T. H., Cabeza, R., Werkle-Bergner, M., & Shing, Y. L. (2018). Age differences in false memory: The importance of retrieval monitoring processes and their modulation by memory quality. Psychology and Aging, 33, 119–133. https://doi.org/10.1037/pag0000212

Wiegand, I., & Sander, M. C. (2018). Cue-related phase reset accounts for age differences in phasic alerting. BioRxiv: 413260. https://doi.org/10.1101/413260

Karch, J. D., Sander, M. C., von Oertzen, T., Brandmaier, A. M., & Werkle-Bergner, M. (2015). Using within-subject pattern classification to understand lifespan age differences in oscillatory mechanisms of working memory selection and maintenance. NeuroImage, 118, 538–552. https://doi.org/10.1016/j.neuroimage.2015.04.038

Fandakova, Y., Sander, M. C., Werkle-Bergner, M., & Shing, Y. L. (2014). Age differences in short-term memory binding are related to working memory performance across the lifespan. Psychology and Aging, 29, 140–149. https://doi.org/10.1037/a0035347

Sander, M. C., Lindenberger, U., & Werkle-Bergner, M. (2012). Lifespan age differences in working memory: A two-component framework. Neuroscience & Biobehavioral Reviews, 36, 2007–2033. https://doi.org/10.1016/j.neubiorev.2012.06.004

Sander, M. C., Werkle-Bergner, M., & Lindenberger, U. (2012). Amplitude modulations and phase-stability of alpha-oscillations differentially reflect working memory constraints across the lifespan. NeuroImage, 59, 646–654. https://doi.org/10.1016/j.neuroimage.2011.06.092

Sander, M. C., Werkle-Bergner, M., Gerjets, P., Shing, Y. L., & Lindenberger, U. (2012). The two-component model of memory development and its potential implications for educational settings. Developmental Cognitive Neuroscience, 2 (Suppl. 1), S67–S77. https://doi.org/10.1016/j.dcn.2011.11.005

Werkle-Bergner, M., Freunberger, R., Sander, M. C., Lindenberger, U., & Klimesch, W. (2012). Inter-individual performance differences in younger and older adults differentially relate to amplitude modulations and phase stability of oscillations controlling working memory contents. NeuroImage, 60, 71–82. https://doi.org/10.1016/j.neuroimage.2011.11.071

Sander, M. C., Werkle-Bergner, M., & Lindenberger, U. (2011). Binding and strategic selection in working memory: A lifespan dissociation. Psychology and Aging, 26, 612–624. https://doi.org/10.1037/a0023055

Sander, M. C., Werkle-Bergner, M., & Lindenberger, U. (2011). Contralateral delay activity reveals lifespan age differences in top-down modulation of working memory contents. Cerebral Cortex, 21, 2809–2819. https://doi.org/10.1093/cercor/bhr076

Team

Myriam C. Sander (Head)

Claudia Wehrspaun (Postdoc)

Anna Karlsson
Verena R. Sommer (Predocs)

Collaboration Partners

MPIB

Yana Fandakova
Markus Werkle-Bergner
Iris Wiegand

Ruhr-UNiversität Bochum

Sarah Weigelt

New

Media

The MERLIN project in which the Minerva Group is involved became part of a short TV report on how the brain learns. It was screened (in German) on ARD alpha in July 2018. Watch it here:
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